Accompanied with continual advancement of communication technologies, a diversity of mobile communication devices, including mobile phones and personal digital assistants (PDAs), are now considered as necessities in the daily life of modern people.
Generally speaking, transmission channels of a wireless mobile communication system are often faced with issues of multiple access interference (MAI) and inter-symbol interference (ISI). The MAI is resulted from multi-user, whereas the ISI is resulted from multi-path-communication quality of the wireless mobile communication system is depreciated from such two issues.
To avoid undesirable effects of the MAI and ISI, a design of rake receivers in a mobile phone is adopted as a common solution. Taking a third-generation (3G) code-division multiple access (CDMA) system for example, a rake receiver implements a correlation of a spread spectrum code to search for delay signals of different paths, and then compensates time and phase of the delay signals. The compensated signals are combined to yield an output result.
FIG. 1 shows a schematic diagram of a structure of a common rake receiver. As shown, upon receiving a signal r(t), the rake receiver multiplies the received signal r(t) by a carrier signal cos(2πf0t). Through associated calculations, the rake receiver separates different delays signals and then removes high-frequency components of the signals using a low-pass filter (LPF) to keep baseband components of the signals. A signal combiner the combines the signals via most common signal combining approaches to yield the output result.
The signal combining approaches, for example, may be equal gain combining (EGC), maximum ratio combining (MRC), selection combining (SC) and other combining approaches. The MRC is multiplying each path with a weight, and the SC discards a path that influences the final output through selection; however, both of the approaches above require an accurate channel model in order to obtain a satisfactory output result. In other words, accuracy of a channel model used plays a critical part in the MRC and SC approaches. Further, the EGC assumes that effects of each of the paths has on the final output result is equal, and yet this assumption does not quite reflect real situations.
FIG. 2 shows a schematic diagram of an original signal o(t) transmitted to a rake receiver. As shown, the original signal o(t) transmitted from a transmitter passes through a transmission channel to reach the rake receiver. In practice, the original signal o(t) is prone to interferences of reflection or refraction from buildings or other objects. Since the original signal o(t) is likely interfered by a noise n(t) before reaching the rake receiver, a signal received by the rake receiver is thus a received signal r(t) interfered by the noise n(t) instead of being the original signal o(t). Therefore, the final output result from the rake receiver is inevitably affected by numerous wireless channel parameters such as time delay, phase, power and path selection. For the sake of convenience, a noise in a conventional channel model is assumed to be additive white Gaussian noise (AWGN); again, such assumption is very different from real situations. Hence, a mobile communication apparatus further utilizes a trial-and-error method or a back-end error calibration method (e.g., turbo codes that are high-performance error correction codes) to reduce its bit error rate. Yet, the error correction methods not only result in large system resource consumption but also jeopardize wireless communication quality.
Therefore, to overcome the issues above, an objective of the present disclosure is to provide a wireless communication system capable of updating current reference channel information, a mobile communication apparatus and a method thereof to overcome the issues associated with the prior art.